This patent relates to a device for measuring the characteristic attitude parameters of a vehicle.
Devices of mechanical type and of optical type are known for measuring said parameters.
Optical devices are known using video cameras positioned in a fixed position with respect to the measurement site on which the vehicle to be checked is located.
Said video cameras monitor a series of targets or locators of known dimensions, each rigid with one of the wheels, and feed the data to a processor which processes the obtained data by means of known trigonometric formulas, to provide on a screen, and possibly by means of a printer, the characteristic attitude parameters of the vehicle, specifically:
left and right front semi-convergence
front total convergence
left and right rear semi-convergence
rear total convergence
right and left front camber
right and left rear camber
right and left incidence
right and left kingpin
front and rear set-back
thrust angle
track difference
The text will be better understood from the following definitions of the characteristic angles:
semi-convergence: the angle formed between the plane perpendicular to the axis of each wheel and the longitudinal axis of symmetry of the vehicle;
total convergence: the angle resulting from the sum of the angles of semi-convergence of the wheels pertaining to one and the same axle;
camber: the angle formed between the plane perpendicular to the axis of each wheel and the vertical plane;
incidence: the angle between the projection of the steering axis onto the vehicle longitudinal plane and the vertical;
kingpin: the angle formed between the projection of the steering axis onto the vehicle transverse plane and the vertical;
set-back: the misalignment between the wheels of one and the same axle and the vehicle axis of symmetry;
thrust axis: the axis between the bisector of the total rear convergence angle and the vehicle axis of symmetry;
track difference: the angle between the line joining the wheels positioned on one and the same side, but pertaining to two different axles, and the vehicle axis of symmetry.
The targets used by said system comprise, in one plane, geometrical patterns formed for example from successions of points, such as point grids, in which the points can be opaque or luminous
The pattern support surfaces and the patterns themselves are known and of known dimensions, and are mounted rigid with the wheels of the vehicles to be examined. A comparison between the known geometrical dimensions and the images received by the video cameras forms the basis for the processing which results in the calculation of the spatial position of the target/wheel.
A system is also known, illustrated in German publication DE 2948573. It comprises a pair of video cameras on each side of the vehicle, each pair being able to be swivelled in order to view the front and rear vehicle wheels alternately.
The video cameras read a target rigid with the wheel, this being the wheel rim edge.
By comparing the images, substantially in the form of ellipses having geometrical characteristics proportional to the wheel inclination, with the reference circle consisting of the wheel rim edge, or by interpolating the images, the characteristic attitude parameters can be determined.
Another known system is illustrated in the documents WO94/05969 and WO97/14016, and comprises a fixed measurement site presenting a frontal rigid bar on which two fixed video cameras are positioned at a predetermined distance apart and are aimed at targets rigid with the vehicle right and left wheels.
By comparing the images acquired by the video cameras with the target sample images, the characteristic attitude parameters can be calculated using known trigonometric calculations.
A system is also known, described in WO01/71280, which uses two alignment video cameras acquiring images of alignment targets of known shape and dimensions fixed to the vehicle front and rear wheels, and a calibration video camera rigid with one of the alignment video cameras to acquire the image of a calibration target of known dimensions rigid with the other alignment video camera.
All the known systems have a common drawback which greatly limits their use, namely the need to use targets of known shape and dimensions.
These targets constitute the sample image with which the known systems compare the target image acquired by the alignment video cameras when the target is fixed to the respective wheel.
It is evident that the known target image must be stored in the memory of the processor which calculates the position of the other targets available to the comparison means, and hence of the wheels.
The said drawback is of considerable importance because it is sufficient for just one of the targets to undergo slight damage, with modification of its image, to render the system inefficient.
Moreover, once the sample image of the known target has been fed into the processor memory, it is not possible to use different targets, even if of known shape and dimensions, without modifying the processor memory data.